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用于脂质管理的医疗保健仪表板技术和数据可视化:范围综述。

Healthcare dashboard technologies and data visualization for lipid management: A scoping review.

机构信息

Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, Australia.

Queensland Digital Health Centre, Faculty of Medicine, The University of Queensland, Brisbane, Australia.

出版信息

BMC Med Inform Decis Mak. 2024 Nov 21;24(1):352. doi: 10.1186/s12911-024-02730-w.

DOI:10.1186/s12911-024-02730-w
PMID:39574106
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11583543/
Abstract

BACKGROUND

Lipid disorders significantly increase cardiovascular disease (CVD) risk, the leading cause of mortality worldwide. Effective lipid management is critical for improving health outcomes. Traditional screening methods face challenges due to data complexity and the need for timely decision-making. Data visualization and dashboard technologies offer clear, actionable insights and supporting informed decision-making. This study investigates the use of these technologies in lipid management and their impacts on the quadruple aim of healthcare.

METHODS

This scoping review followed the Joanna Briggs Institute (JBI) approach, focusing on studies involving dashboard technologies or data visualization in lipid management. A comprehensive search across multiple databases (Embase, Web of Science, PubMed, Scopus, CINAHL) and gray literature was conducted, including English-language publications from 2014 to 2024. Data were analyzed using quantitative descriptive and qualitative content analysis to evaluate the key features, clinical applications, and outcomes.

RESULTS

Twenty-seven studies met the inclusion criteria, primarily focusing on dashboard utilization by physicians for managing diabetes and CVD, utilizing electronic medical records and clinical guidelines. Key analysis methods included comparing key performance indicators (KPIs) (85.2%) and trend analysis (74.1%). Lipid management workflows emphasized prevention (88.9%) and treatment planning (77.8%). Interventions included care packages (comprehensive sets of interventions for patient care), decision support systems, web-based tools, and mobile health solutions. Regarding Quadruple Aim outcomes: 12 studies focused on improving population health (8 positive, 4 no change), 9 on clinical outcomes (5 positive, 4 no change), 6 on provider work life (5 positive), 5 on patient experience (positive changes in education and time management), and 2 on cost reduction (1 positive, 1 negative).

CONCLUSIONS

Dashboards are important tools in managing lipid disorders in managing lipid disorders, integrating with educational tools, collaborative care models, and decision support systems. Although they are effective in enhancing population health and clinical experiences, their impact on patient outcomes and cost reduction requires further exploration. Future research should focus on detailed evaluations of dashboard impacts on patient outcomes and cost-effectiveness, emphasizing precision prevention of chronic diseases.

摘要

背景

血脂异常显著增加心血管疾病(CVD)风险,是全球主要的死亡原因。有效的血脂管理对于改善健康结果至关重要。由于数据的复杂性和及时决策的需要,传统的筛选方法面临挑战。数据可视化和仪表板技术提供了清晰、可操作的见解,并支持做出明智的决策。本研究调查了这些技术在血脂管理中的应用及其对医疗保健四重目标的影响。

方法

本范围综述遵循乔安娜·布里格斯研究所(JBI)的方法,重点关注涉及血脂管理中仪表板技术或数据可视化的研究。在多个数据库(Embase、Web of Science、PubMed、Scopus、CINAHL)和灰色文献中进行了全面搜索,包括 2014 年至 2024 年期间发表的英文文献。使用定量描述性和定性内容分析来分析数据,以评估关键特征、临床应用和结果。

结果

符合纳入标准的研究有 27 项,主要侧重于医生使用仪表板管理糖尿病和 CVD,利用电子病历和临床指南。关键分析方法包括比较关键绩效指标(KPI)(85.2%)和趋势分析(74.1%)。血脂管理工作流程强调预防(88.9%)和治疗计划(77.8%)。干预措施包括护理包(患者护理的综合干预措施)、决策支持系统、基于网络的工具和移动健康解决方案。关于四重目标结果:12 项研究侧重于改善人群健康(8 项积极,4 项无变化),9 项研究侧重于临床结果(5 项积极,4 项无变化),6 项研究侧重于提供者的工作生活(5 项积极),5 项研究侧重于患者体验(教育和时间管理方面的积极变化),2 项研究侧重于降低成本(1 项积极,1 项消极)。

结论

仪表板是管理血脂紊乱的重要工具,与教育工具、协作护理模式和决策支持系统集成。尽管它们在提高人群健康和临床体验方面非常有效,但它们对患者结果和降低成本的影响需要进一步探讨。未来的研究应侧重于详细评估仪表板对患者结果和成本效益的影响,强调慢性病的精准预防。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f84/11583543/454fc76f8bb4/12911_2024_2730_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f84/11583543/852a100db5d7/12911_2024_2730_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f84/11583543/454fc76f8bb4/12911_2024_2730_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f84/11583543/852a100db5d7/12911_2024_2730_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f84/11583543/454fc76f8bb4/12911_2024_2730_Fig2_HTML.jpg

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